Database constraints are rules enforced on data in a database to ensure its accuracy, integrity, and reliability. They prevent invalid data entry and maintain data consistency across the database system by defining specific conditions that data must meet before being stored.

Database Constraint

Database constraints are rules applied to database tables to ensure the accuracy and reliability of the data within. They enforce data integrity by limiting the types of data that can be inserted, updated, or deleted, thus preventing invalid data entry and maintaining consistency across the database.

Database constraints

rules enforced on data

Data accuracy refers to the closeness of data to the true values or the intended representation of those values, ensuring reliability and validity in decision-making processes. High data accuracy is crucial for effective analysis, forecasting, and maintaining trust in data-driven insights.

Data Accuracy

Data integrity refers to the accuracy, consistency, and reliability of data throughout its lifecycle, ensuring that it remains unaltered and trustworthy for decision-making and analysis. It is crucial for maintaining the credibility of databases and information systems, and involves various practices and technologies to prevent unauthorized access or corruption.

Data Integrity

Data reliability refers to the consistency and dependability of data over time, ensuring that it is accurate, complete, and can be trusted for decision-making. High data reliability minimizes errors and biases, which is crucial for effective analysis and meaningful insights.

Data Reliability

invalid data entry

Data consistency ensures that data remains accurate and reliable across a system, preventing discrepancies and errors during data processing and retrieval. It is crucial for maintaining data integrity, especially in distributed systems where multiple sources may update the same data concurrently.

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